1. Field of the Invention
The present invention relates to a method for adjusting an image signal by a processor, and more specifically, to a method for image processing by unsharp masking.
2. Description of the Prior Art
Please refer to FIG. 1 and FIG. 2. FIG. 1 is a block diagram illustrating a conventional image processing system 10 and FIG. 2 illustrates an image 14 of the image processing system 10 in FIG. 1. The image processing system 10 includes a memory 12 for storing programs and the image 14 to be processed, and a processor 16 for executing the programs stored in the memory 12. The image 14 includes a plurality of pixels 18 arranged in matrix form. The image 14 is composed of an image area 20 with specific features and a boundary area 22 around the image area 20.
A goal of image processing is to have the features of the image area 20 stand out while keeping the image area 20 and the surrounding edge area 22 in harmony. An adjustment of the image parameters of the whole image 14 will sacrifice some features that are not within the image area 20 or cause distortion of the image area 20. For this reason, some image processing methods adjust only the image parameters of the surrounding edge area 22 in order to emphasize the high frequency characteristic of the edge of the image.
The unsharp mask method is a method based on the concept mentioned above. According to the method, first unsharpen an image to obtain a low frequency element of the image, then subtract the unsharpened image from the original image to obtain a high frequency element of the original image. Apply a convolution operation to the remaining high frequency image and eventually add the subtracted low frequency image to the remaining high frequency image to complete the process. Although the unsharp mask method can sharpen the edge of the image, it also increases the high frequency element of the image and raises the luminance of the whole image, making it lighter. In addition, according to the conventional unsharp mask method, while applying the convolution operation to the high frequency image and adding back the subtracted low frequency image, because two operation intensive calculations are required to be processed simultaneously, processing time and image processing cost are increased.